Joined January 2017
- Tweets 92
- Following 283
- Followers 113
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6 Photos and videos
Pinned Tweet
15 Feb 2023
Very happy to share that I have been awarded a @MSCActions Postdoctoral Fellowship. The #EU has funded our project, which aims to develop a high-throughput strategy to discover novel catalysts for the hydrogen economy by combining #compchem and #ML
15 Feb 2023
1/4...IMDEA Materials scores unprecedented success in MSCA #Fellowship call! We are pleased to announce that we have been awarded six @MSCActions #Postdoctoral Fellowships.
You can read more, here: materials.imdea.org/imdea-ma…
@MSCANetwork @EU_Commission
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Valentin Vassilev-Galindo retweeted
20 Aug 2025
Our symposium on #ML for #materials at #IMRC2025 went great - big thanks to my fellow co-organisers @HESauceda and @theochemmerida, and 👏🏻 to the amazing speakers Claudia Draxl, Alex Tkatchenko, Qian Yang, @_ValentinVG, and others. Proud to reach gender parity in talks!
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19 Jul 2024
This week, I attended the @ICCLyon2024 conference in Lyon, the biggest event gathering researchers and industries working on catalysis. There, I presented the work we have been doing within the @MSCActions #HighHydrogenML project. @ImdeaMaterials
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4 Jul 2024
Glad to share our work, where we apply #ML to predict the adsorption energy of H, O, and OH on bimetallic materials considering the effects of elastic strains. Screening of new potential catalysts is possible. @MSCActions #HighHydrogenML @ImdeaMaterials pubs.rsc.org/en/content/arti…
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7 Jun 2024
This week, I presented our work on #ML and #CompChem for discovering new catalysts for the hydrogen economy at @espa2024 in the beautiful city of Tarragona. There were many interesting talks and poster presentations, as well as fruitful discussions. @ImdeaMaterials @MSCActions
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Valentin Vassilev-Galindo retweeted
7 Jun 2024
Using the participation of the d orbitals in heavy Group 2 elements, it is possible to stabilize planar pentadecacoordinate atoms. This is the story we detailed in our recent article published in @J_A_C_S
A collaboration between groups in 🇨🇳 🇨🇱 🇺🇸 🇲🇽
pubs.acs.org/doi/10.1021/jac…
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Valentin Vassilev-Galindo retweeted
6 Jun 2024
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Valentin Vassilev-Galindo retweeted
21 May 2024
I am delighted to share our latest work in collaboration with @TCPUniLu! Join us as we explore the world of Explainable Chemical Artificial Intelligence (XCAI) using real-space chemistry! nature.com/articles/s41467-0…
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Valentin Vassilev-Galindo retweeted
22 May 2024
Check out our new paper rdcu.be/dIA5D on Explainable Chemical Artificial Intelligence using real-space descriptors now published in Nat. Commun. Great collaboration with @TCPUniLu and colophon of Miguel Gallegos' PhD Thesis. #compchem @uniovi_info @Fac_Quim_Uniovi
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1 Feb 2024
Happy to share my first work at @ImdeaMaterials. We unveil through #ML that many-body microstructural features in Mg alloys have a crucial role on the nucleation of extension twins in grains unfavorably oriented for twinning. @Nature_NPJ Read more: nature.com/articles/s41524-0…
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Valentin Vassilev-Galindo retweeted
15 Jan 2024
⏳ There is just one month left to apply for the #BIOMEND - Doctorate Network!
We are excited to be collaborating in this initiative, with applications open for 15 #PhD candidates in BIOabsorbable Metallic ENdovascular Medical Devices.
Full details ➡️biomend.eu/
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Valentin Vassilev-Galindo retweeted
11 Jan 2024
📽️ El periodista Iñaki Rodríguez de @La1_tve habla con el cofundador de @Floatech, el Dr. Juan José Vilatela, y la ingeniera de procesos María Murillo Vidal, sobre los planes de la start up de abrir una planta piloto en Madrid en los próximos tres meses 👏
@ComunidadMadrid
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Valentin Vassilev-Galindo retweeted
3 Oct 2023
BREAKING NEWS
The Royal Swedish Academy of Sciences has decided to award the 2023 #NobelPrize in Physics to Pierre Agostini, Ferenc Krausz and Anne L’Huillier “for experimental methods that generate attosecond pulses of light for the study of electron dynamics in matter.”
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23 Sep 2023
It was very exciting to contribute! Congrats to all for the great work!
Not just one, but TWO of our recent reviews are now featured in the @ACSChemRev's top 20 most-read articles over the past year, with 50k and 60k views respectively 📚🔥
Check them out here:
doi.org/10.1021/acs.chemrev.…
doi.org/10.1021/acs.chemrev.…
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Valentin Vassilev-Galindo retweeted
4 Sep 2023
From “Freedom of Design” to the actual inverse design of molecules with targeted quantum-mechanical properties!😃
arxiv.org/abs/2309.00506
👉Have a look at our recent preprint where we parametrize QM7-X chemical space with a set of QM properties.
@SuperFalla @TCPUniLu @AiddOne
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Valentin Vassilev-Galindo retweeted
14 Jul 2023
It was good fun to write that review with @hbdft2008 and @ProfvLilienfeld!
➡️ML is data-limited, and DFT likely is the way out
➡️Data is too scarce, e.g. for excited states, non-equilibrium geometries, charged systems and more elements
There's Plenty of Room at the Bottom😉
13 Jul 2023
Nice review by Bing Huang, @ferchault, and @ProfvLilienfeld on just how important DFT is to the future of AI for molecules.
Still so many open questions (especially in biophysics) but quantum chemistry is definitely a fundamental part of the equation!
science.org/doi/10.1126/scie…
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Valentin Vassilev-Galindo retweeted
21 Jun 2023
Lightning-fast QTAIM charges and more with NNAIMGUI. #compchem Take a look at pubs.acs.org/doi/10.1021/acs…
Code at github.com/m-gallegos/NNAIMG…
@jcim_jctc @uniovi_info
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Valentin Vassilev-Galindo retweeted
16 Jun 2023
👏 IMDEA Materials Institute is greatly looking forward to the debut of the HERA project at next week's @parisairshow!
✈️ HERA is developing the next hybrid electric regional passenger aircraft with the aim of reducing emissions by up to 90%.
info: youtube.com/watch?v=nPctr_Bh…
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15 Jun 2023
Don't miss the opportunity to read our work, where we implement many-body expansions into GDML for constructing a size-transferable #MachineLearning force field. #CompChem
14 Jun 2023
Tkatchenko, Keith, et. al., present a gradient-domain ML force field trained on many-body interactions, to create a size-transferable force field: mbGDML. Get the full picture in today's featured #openaccess advance article: doi.org/10.1039/D3DD00011G
ALT One- two- and three-body datasets on water are used to generate corresponding ML force fields, which are then used in modeling a quantity of water molecules. GDML is trained using a smaller number of of data sets than NN.
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Valentin Vassilev-Galindo retweeted
5 Jun 2023
🎦 For those that missed it in person, you can now view our "Being a Marie Skłodowska-Curie Actions Postdoctoral Fellow at IMDEA Materials Institute" webinar on our YouTube page following the link ⬇️
youtube.com/watch?v=e4FZaOtW…
@_ValentinVG, @crisgomez55, @germaninf, @FECYT_Ciencia
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